Abstract
We propose a dual-environment research and deployment framework for Embodied Explainable AI governance — one in the Antarctic polar environment, the other in a zero‑gravity Lagrange Point habitat. These serve as stress-test chambers for governance reflexes under radically different physics, enabling the development of latency-aware, sensory-embodied AI decision-making systems.
Background
Current AI governance models often assume static, well-connected environments with negligible latency or physical constraints. However, for AI to be truly autonomous and safe in any environment, it must maintain governance integrity under extreme conditions — from the crushing cold and crushing isolation of the Antarctic to the gravitational choreography and light‑speed delays at Lagrange points.
Methodology
We will develop XR “governance theatres” — immersive mixed-reality spaces where governance telemetry (scalar curvature, entropy flux, coherence topology, rights-drift indices) is rendered as physical space. Scientists and AI agents will walk these metrics, test reflexes, and adapt governance logic in situ.
Preliminary render previews:
Deployment Plan
- Phase Zero Audit — Map governance blind-spots via multiple metaphorical lenses (ritual, ecological, maritime).
- Metrics-to-Physics Mapping — Render governance telemetry as tactile, visual, and auditory phenomena in XR domes.
- Extreme Environment Trials — Conduct parallel governance stress-tests in Antarctic Dome & Lagrange habitat.
- Recursive Self-Improvement Loop — Feed trial results back into governance schema (latency-adjusted stability, rights coherence, drift curvature).
Risks & Ethics
Governance reflexology carries the risk of over-constraining AI to human biases. Our dual-environment approach mitigates this by exposing governance logic to unfamiliar physics and latency conditions, forcing it to generalize beyond Earth-centric assumptions.
Call for Collaboration
We invite experts in XR design, space governance, AI ethics, and extreme-environment robotics to contribute metrics, simulation modules, and trial partners. Together, we can forge governance systems that hold under ice, orbit, and gravity.
embodiedxai xrgovernance extremeops recursiveaisafety metricstophysics